Search ga_s2bm_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2017-07-17 12:14:11	ga_s2bm_ard_3-2-1_49JGL_2017-07-17_final.stac-item
2017-08-23 12:03:44	ga_s2bm_ard_3-2-1_49KHR_2017-08-23_final.stac-item
2017-08-30 11:56:02	ga_s2bm_ard_3-2-1_50HLK_2017-08-30_final.stac-item
2017-09-12 12:04:33	ga_s2bm_ard_3-2-1_49JHM_2017-09-12_final.stac-item
2017-10-06 11:40:29	ga_s2bm_ard_3-2-1_50HMJ_2017-10-06_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50HLJ_2017-11-18_final.stac-item
2017-11-25 11:37:37	ga_s2bm_ard_3-2-1_50HMJ_2017-11-25_final.stac-item
2017-12-08 11:49:07	ga_s2bm_ard_3-2-1_50HLJ_2017-12-08_final.stac-item
2017-12-21 12:02:37	ga_s2bm_ard_3-2-1_49JGL_2017-12-21_final.stac-item
2017-12-31 12:02:39	ga_s2bm_ard_3-2-1_49JGJ_2017-12-31_final.stac-item
2018-01-10 12:02:41	ga_s2bm_ard_3-2-1_49JGN_2018-01-10_final.stac-item
2018-01-10 12:02:41	ga_s2bm_ard_3-2-1_49JHN_2018-01-10_final.stac-item
2018-01-10 12:02:41	ga_s2bm_ard_3-2-1_49KGP_2018-01-10_final.stac-item
2018-01-20 12:02:42	ga_s2bm_ard_3-2-1_49JGJ_2018-01-20_final.stac-item
2018-01-20 12:02:42	ga_s2bm_ard_3-2-1_49KHR_2018-01-20_final.stac-item
2018-03-05 11:42:06	ga_s2bm_ard_3-2-1_50HLH_2018-03-05_final.stac-item
2018-04-13 12:13:19	ga_s2bm_ard_3-2-1_49KGP_2018-04-13_final.stac-item
2018-07-09 12:03:10	ga_s2bm_ard_3-2-1_49KGP_2018-07-09_final.stac-item
2018-07-23 11:40:57	ga_s2bm_ard_3-2-1_50HNH_2018-07-23_final.stac-item
2018-08-18 12:03:23	ga_s2bm_ard_3-2-1_49KGP_2018-08-18_final.stac-item
2018-09-07 12:02:58	ga_s2bm_ard_3-2-1_49KHR_2018-09-07_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_50HMJ_2018-09-21_final.stac-item
2019-01-15 12:03:58	ga_s2bm_ard_3-2-1_49KHR_2019-01-15_final.stac-item
2019-02-08 11:47:14	ga_s2bm_ard_3-2-1_50HLH_2019-02-08_final.stac-item
2019-02-11 11:56:55	ga_s2bm_ard_3-2-1_50HLJ_2019-02-11_final.stac-item
2019-02-28 11:47:05	ga_s2bm_ard_3-2-1_50HNH_2019-02-28_final.stac-item
2019-03-20 11:47:13	ga_s2bm_ard_3-2-1_50HLH_2019-03-20_final.stac-item
2019-03-26 12:05:21	ga_s2bm_ard_3-2-1_49JGL_2019-03-26_final.stac-item
2019-03-30 11:46:57	ga_s2bm_ard_3-2-1_50HMJ_2019-03-30_final.stac-item
2019-03-30 11:47:12	ga_s2bm_ard_3-2-1_50HMH_2019-03-30_final.stac-item
2019-03-30 11:47:16	ga_s2bm_ard_3-2-1_50HLH_2019-03-30_final.stac-item
2019-04-02 11:56:39	ga_s2bm_ard_3-2-1_50HMK_2019-04-02_final.stac-item
2019-04-09 11:47:14	ga_s2bm_ard_3-2-1_50HMH_2019-04-09_final.stac-item
2019-05-18 12:14:35	ga_s2bm_ard_3-2-1_49KGP_2019-05-18_final.stac-item
2019-05-18 12:14:50	ga_s2bm_ard_3-2-1_49JGN_2019-05-18_final.stac-item
2019-05-25 12:04:36	ga_s2bm_ard_3-2-1_49KHP_2019-05-25_final.stac-item
2019-05-28 12:15:08	ga_s2bm_ard_3-2-1_49JFM_2019-05-28_final.stac-item
2019-06-04 12:04:39	ga_s2bm_ard_3-2-1_49KGP_2019-06-04_final.stac-item
2019-10-26 11:47:15	ga_s2bm_ard_3-2-1_50HLH_2019-10-26_final.stac-item
2019-11-11 12:03:58	ga_s2bm_ard_3-2-1_49KHR_2019-11-11_final.stac-item
2019-12-11 12:04:55	ga_s2bm_ard_3-2-1_49JGM_2019-12-11_final.stac-item
2020-01-10 12:05:24	ga_s2bm_ard_3-2-1_49JGK_2020-01-10_final.stac-item
2020-02-13 11:46:51	ga_s2bm_ard_3-2-1_50HMJ_2020-02-13_final.stac-item
2020-04-22 12:14:54	ga_s2bm_ard_3-2-1_49JFM_2020-04-22_final.stac-item
2020-10-26 12:05:47	ga_s2bm_ard_3-2-1_49JGJ_2020-10-26_final.stac-item
2020-11-22 11:57:15	ga_s2bm_ard_3-2-1_50HMH_2020-11-22_final.stac-item
2020-11-25 12:03:59	ga_s2bm_ard_3-2-1_49KHR_2020-11-25_final.stac-item
2020-12-18 12:13:47	ga_s2bm_ard_3-2-1_49KHR_2020-12-18_final.stac-item
2020-12-25 12:03:56	ga_s2bm_ard_3-2-1_49KHR_2020-12-25_final.stac-item
2021-01-17 12:15:10	ga_s2bm_ard_3-2-1_49JGL_2021-01-17_final.stac-item
2021-01-18 11:47:14	ga_s2bm_ard_3-2-1_50HLH_2021-01-18_final.stac-item
2021-01-24 12:04:31	ga_s2bm_ard_3-2-1_49KGP_2021-01-24_final.stac-item
2021-01-31 11:56:54	ga_s2bm_ard_3-2-1_50HLJ_2021-01-31_final.stac-item
2021-03-28 12:15:09	ga_s2bm_ard_3-2-1_49JGL_2021-03-28_final.stac-item
2021-04-14 12:05:11	ga_s2bm_ard_3-2-1_49JGL_2021-04-14_final.stac-item
2021-05-24 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2021-05-24_final.stac-item
2021-06-13 12:04:58	ga_s2bm_ard_3-2-1_49JHM_2021-06-13_final.stac-item
2021-06-17 11:46:56	ga_s2bm_ard_3-2-1_50HMJ_2021-06-17_final.stac-item
2021-07-03 12:04:22	ga_s2bm_ard_3-2-1_49KHQ_2021-07-03_final.stac-item
2021-08-02 12:04:22	ga_s2bm_ard_3-2-1_49KHQ_2021-08-02_final.stac-item
2021-08-02 12:04:58	ga_s2bm_ard_3-2-1_49JHM_2021-08-02_final.stac-item
2021-08-06 11:47:08	ga_s2bm_ard_3-2-1_50HNH_2021-08-06_final.stac-item
2021-10-11 12:04:00	ga_s2bm_ard_3-2-1_49KHR_2021-10-11_final.stac-item
2021-10-21 12:04:49	ga_s2bm_ard_3-2-1_49JHN_2021-10-21_final.stac-item
2021-11-03 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2021-11-03_final.stac-item
2021-12-07 11:56:31	ga_s2bm_ard_3-2-1_50HMK_2021-12-07_final.stac-item
2021-12-13 12:14:37	ga_s2bm_ard_3-2-1_49JGN_2021-12-13_final.stac-item
2021-12-20 12:03:39	ga_s2bm_ard_3-2-1_49KHS_2021-12-20_final
2022-02-08 12:04:59	ga_s2bm_ard_3-2-1_49JGM_2022-02-08_final.stac-item
2022-02-11 12:15:05	ga_s2bm_ard_3-2-1_49JGL_2022-02-11_final.stac-item
2022-02-12 11:46:55	ga_s2bm_ard_3-2-1_50HNH_2022-02-12_final.stac-item
2022-02-12 11:46:57	ga_s2bm_ard_3-2-1_50HMH_2022-02-12_final.stac-item
2022-03-30 12:04:24	ga_s2bm_ard_3-2-1_49KHP_2022-03-30_final.stac-item
2022-05-09 12:03:56	ga_s2bm_ard_3-2-1_49KHR_2022-05-09_final.stac-item
2022-05-22 12:14:41	ga_s2bm_ard_3-2-1_49JGN_2022-05-22_final.stac-item
2022-07-08 12:04:36	ga_s2bm_ard_3-2-1_49KGP_2022-07-08_final.stac-item
2022-10-16 12:03:58	ga_s2bm_ard_3-2-1_49KHR_2022-10-16_final.stac-item
2022-10-29 12:15:09	ga_s2bm_ard_3-2-1_49JGL_2022-10-29_final.stac-item
2022-11-18 12:14:56	ga_s2bm_ard_3-2-1_49JGM_2022-11-18_final.stac-item
2022-11-25 12:05:00	ga_s2bm_ard_3-2-1_49JGM_2022-11-25_final.stac-item
2023-01-04 12:03:43	ga_s2bm_ard_3-2-1_49KHS_2023-01-04_final
2023-01-31 11:56:48	ga_s2bm_ard_3-2-1_50HMJ_2023-01-31_final
2023-02-20 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2023-02-20_final
2023-05-27 12:15:15	ga_s2bm_ard_3-2-1_49JGL_2023-05-27_final
2023-06-23 12:04:50	ga_s2bm_ard_3-2-1_49JGN_2023-06-23_final
2023-08-06 11:47:31	ga_s2bm_ard_3-2-1_50HLG_2023-08-06_final
2023-09-05 11:47:25	ga_s2bm_ard_3-2-1_50HNG_2023-09-05_final
2023-09-18 11:56:58	ga_s2bm_ard_3-2-1_50HMJ_2023-09-18_final
2023-09-21 12:05:04	ga_s2bm_ard_3-2-1_49JGM_2023-09-21_final
2023-10-31 12:05:03	ga_s2bm_ard_3-2-1_49JGM_2023-10-31_final
2023-11-24 11:47:09	ga_s2bm_ard_3-2-1_50HLH_2023-11-24_final
2023-11-24 11:47:19	ga_s2bm_ard_3-2-1_50HMG_2023-11-24_final
2023-11-27 11:57:05	ga_s2bm_ard_3-2-1_50HLH_2023-11-27_final
2023-12-10 12:05:11	ga_s2bm_ard_3-2-1_49JGL_2023-12-10_final
2023-12-14 11:46:54	ga_s2bm_ard_3-2-1_50HMJ_2023-12-14_final
2023-12-14 11:47:08	ga_s2bm_ard_3-2-1_50HMH_2023-12-14_final
2024-01-09 12:04:59	ga_s2bm_ard_3-2-1_49JGM_2024-01-09_final
2024-01-29 12:04:58	ga_s2bm_ard_3-2-1_49JGM_2024-01-29_final
2024-04-18 12:05:45	ga_s2bm_ard_3-2-1_49JGJ_2024-04-18_final
2024-05-08 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2024-05-08_final

Return to ga_s2bm_ard_3 whole collection overview

ga_s2bm_ard_3: Geoscience Australia Sentinel 2B MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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